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Found 2 papers, 1 papers with code
FedGS: Federated Graph-based Sampling with Arbitrary Client Availability
Second, constrained by the far-distance in data distribution of the sampled clients, we further minimize the variance of the numbers of times that the clients are sampled, to mitigate long-term bias.
Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting
However, this approach failed to explicitly reflect the correlations between different nodes at different time steps, thus limiting the learning capability of graph neural networks.
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